@article {32157, title = {Assessment of occupant-behavior-based indoor air quality and its impacts on human exposure risk: A case study based on the wildfires in Northern California}, journal = {Science of The Total Environment}, volume = {686}, year = {2019}, month = {Jan-10-2019}, pages = {1251 - 1261}, abstract = {

The recent wildfires in California, U.S., have caused not only significant losses to human life and property, but also serious environmental and health issues. Ambient air pollution from combustion during the fires could increase indoor exposure risks to toxic gases and particles, further exacerbating respiratory conditions. This work aims at addressing existing knowledge gaps in understanding how indoor air quality is affected by outdoor air pollutants during wildfires{\textemdash}by taking into account occupant behaviors (e.g., movement, operation of windows and air-conditioning) which strongly influence building performance and occupant comfort. A novel modeling framework was developed to simulate the indoor exposure risks considering the impact of occupant behaviours by integrating building energy and occupant behaviour modeling with computational fluid dynamics simulation. Occupant behaviors were found to exert significant impacts on indoor air flow patterns and pollutant concentrations, based on which, certain behaviors are recommended during wildfires. Further, the actual respiratory injury level under such outdoor conditions was predicted. The modeling framework and the findings enable a deeper understanding of the actual health impacts of wildfires, as well as informing strategies for mitigating occupant health risk during wildfires

}, keywords = {computational fluid dynamics siumlation, human exposure risk, indoor air quality, NAPA wildfire, occupant behavior, respiratory injury}, issn = {00489697}, doi = {10.1016/j.scitotenv.2019.05.467}, author = {Luo, Na and Weng, Wenguo and Xu, Xiaoyu and Tianzhen Hong and Fu, Ming and Sun, Kaiyu} } @article {32160, title = {Cross-source sensing data fusion for building occupancy prediction with adaptive lasso feature filtering}, journal = {Building and Environment}, volume = {162}, year = {2019}, month = {Jan-09-2019}, pages = {106280}, abstract = {

Fusing various sensing data sources can significantly improve the accuracy and reliability of building occupancy detection. Fusing environmental sensors and wireless network signals are seldom studied for its computational and technical complexity. This study aims to propose an integrated adaptive lasso model that is able to extract critical data features for environmental and Wi-Fi probe dual sensing sources. Through rapid feature extraction and process simplification, the proposed method aims to improve the computational efficiency of occupancy detecting models. To validate the proposed model, an onsite experiment was conducted to examine two occupancy data resolutions, (real-time and four-level occupancy resolutions). The results suggested that, among all twelve features, eight features are most relevant. The mean absolute error of the real-time occupancy can be reduced to 2.18 and F1_accuracy is about 84.36\% for the four-level occupancy.

}, keywords = {data fusion, Feature selection, Machine learning, occupancy prediction, Physics-based model}, issn = {03601323}, doi = {10.1016/j.buildenv.2019.106280}, author = {Wang, Wei and Tianzhen Hong and Xu, Ning and Xu, Xiaodong and Chen, Jiayu and Shan, Xiaofang} } @article {31670, title = {Forecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm}, journal = {Applied Energy}, volume = {248}, year = {2019}, month = {04/2019}, pages = {217 - 230}, abstract = {

With the development of data-driven techniques, district-scale building energy prediction has attracted increasing attention in recent years for revealing energy use patterns and reduction potentials. However, data acquisition in large building groups is difficult and adjacent buildings also interact with each other. To reduce data cost and incorporate the inter-building impact with the data-driven building energy model, this study proposes a deep learning predictive approach that fuses the building network model with a long short-term memory learning model for district-scale building energy modeling. The building network was constructed based on correlations between the energy use intensity of buildings, which can significantly reduce the computational complexity of the deep learning models for energy dynamic prediction. Five typical building groups with energy use data from 2015 to 2018 on two institutional campuses were selected to perform the validation experiment with TensorFlow. Based on the prediction error assessments, the results suggest that for total building energy use intensity prediction, the proposed model can achieve a mean absolute percentage error of 6.66\% and a root mean square error of 0.36 kWh/m2, compared to 12.05\% and 0.63 kWh/m2 of the conventional artificial neural network model and to 11.06\% and 0.89 kWh/m2 for the support vector regression model.

}, keywords = {Building Energy Modeling, Building network, Data-driven prediction, District-scale, Long short-term memory networks}, issn = {03062619}, doi = {10.1016/j.apenergy.2019.04.085}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0306261919307494}, author = {Wei Wang and Tianzhen Hong and Xiaodong Xu and Jiayu Chen and Ziang Liu and Ning Xu} } @article {31665, title = {Incorporating machine learning with building network analysis to predict multi-building energy use}, journal = {Energy and Buildings}, volume = {186}, year = {2019}, month = {06/2019}, pages = {80 - 97}, abstract = {

Predicting multi-building energy use at campus or city district scale has recently gained more attention; and more researchers have started to define reference buildings and study inter-impact between building groups. However, how to integrate the relationship to define reference buildings and predict multi-building energy use, using significantly less amount of building data and reducing complexity of prediction models, remains an open research question. To resolve this, this study proposed a novel method to predict multi-building energy use by integrating a social network analysis (SNA) with an Artificial Neural Network (ANN) technique. The SNA method was used to establish a building network (BN) by identifying reference buildings and determine correlations between reference buildings and non-reference buildings. The ANN technique was applied to learn correlations and historical building energy use, and then used to predict multi-building energy use. To validate the SNA-ANN method, 17 buildings in the Southeast University campus, located in Nanjing, China, were studied. These buildings have three years of actual monthly electricity use data and were grouped into four types: office, educational, laboratory, and residential. The results showed the integrated SNA-ANN method achieved average prediction accuracies of 90.67\% for the office group, 90.79\% for the educational group, 92.34\% for the laboratory group, and 83.32\% for the residential group. The results demonstrated the proposed SNA-ANN method achieved an accuracy of 90.28\% for the predicted energy use for all building groups. Finally, this study provides insights into advancing the interdisciplinary research on multi-building energy use prediction.

}, keywords = {Artificial neural networks, Building network, cold winter and hot summer climate, Energy use prediction, Machine learning}, issn = {03787788}, doi = {10.1016/j.enbuild.2019.01.002}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0378778818319765}, author = {Xiaodong Xu and Wei Wang and Tianzhen Hong and Jiayu Chen} } @article {31669, title = {A novel approach for selecting typical hot-year (THY) weather data}, journal = {Applied Energy}, volume = {242}, year = {2019}, month = {03/2019}, pages = {1634 - 1648}, abstract = {

The global climate change has resulted in not only warmer climate conditions but also more frequent extreme weather events, such as heat waves. However, the impact of heat waves on the indoor environment has been investigated in a limited manner. In this research, the indoor thermal environment is analyzed using a building performance simulation tool for a typical residential building in multiple cities in China, over a time period of 60 years using actual measured weather data, in order to gain a better understanding of the effect of heat wave events. The simulation results were used to analyze the indoor environment during hot summers. A new kind of weather data referred to as the typical hot year was defined and selected based on the simulated indoor environment during heat waves. The typical hot-year weather data can be used to simulate the indoor environment during extreme heat events and for the evaluation of effective technologies and strategies to mitigate against the impact of heat waves on the energy demand of buildings and human health. The limitations of the current study and future work are also discussed.

}, keywords = {Actual weather data, dest, Heat wave, Multiyear simulation, Residential indoor thermal environment, Typical hot year}, issn = {03062619}, doi = {10.1016/j.apenergy.2019.03.065}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0306261919304659}, author = {Siyue Guo and Da Yan and Tianzhen Hong and Chan Xiao and Ying Cui} } @article {31664, title = {Performance-driven optimization of urban open space configuration in the cold-winter and hot-summer region of China}, journal = {Building Simulation}, volume = {12}, year = {2019}, month = {03/2019}, pages = {411 - 424}, abstract = {

Urbanization has led to changes in urban morphology and climate, while urban open space has become an important ecological factor for evaluating the performance of urban development. This study presents an optimization approach using computational performance simulation. With a genetic algorithm using the Grasshopper tool, this study analyzed the layout and configuration of urban open space and its impact on the urban micro-climate under summer and winter conditions. The outdoor mean Universal Thermal Climate Index (UTCI) was applied as the performance indicator for evaluating the quality of the urban micro-climate. Two cases{\textemdash}one testbed and one real urban block in Nanjing, China{\textemdash}were used to validate the computer-aided simulation process. The optimization results in the testbed showed UTCI values varied from 36.5 to 37.3 {\textdegree}C in summer and from -4.9 to -1.9 {\textdegree}C in winter. In the case of the real urban block, optimization results show, for summer, although the average UTCI value increased by 0.6 {\textdegree}C, the average air velocity increased by 0.2 m/s; while in winter, the average UTCI value increased by 1.7 {\textdegree}C and the average air velocity decreased by 0.2 m/s. These results demonstrate that the proposed computer-aided optimization process can improve the thermal comfort conditions of open space in urban blocks. Finally, this study discusses strategies and guidelines for the layout design of urban open space to improve urban environment comfort.

}, issn = {1996-3599}, doi = {10.1007/s12273-019-0510-z}, url = {http://link.springer.com/10.1007/s12273-019-0510-zhttp://link.springer.com/content/pdf/10.1007/s12273-019-0510-z.pdfhttp://link.springer.com/content/pdf/10.1007/s12273-019-0510-z.pdfhttp://link.springer.com/article/10.1007/s12273-019-0510-z/fulltext.html}, author = {Xiaodong Xu and Yifan Wu and Wei Wang and Tianzhen Hong and Ning Xu} } @article {32159, title = {Revealing Urban Morphology and Outdoor Comfort through Genetic Algorithm-Driven Urban Block Design in Dry and Hot Regions of China}, journal = {Sustainability}, volume = {11}, year = {2019}, month = {Jan-07-2019}, pages = {3683}, abstract = {

In areas with a dry and hot climate, factors such as strong solar radiation, high temperature, low humidity, dazzling light, and dust storms can tremendously reduce people{\textquoteright}s thermal comfort. Therefore, researchers are paying more attention to outdoor thermal comfort in urban environments as part of urban design. This study proposed an automatic workflow to optimize urban spatial forms with the aim of improvement of outdoor thermal comfort conditions, characterized by the universal thermal climate index (UTCI). A city with a dry and hot climate{\textemdash}Kashgar, China{\textemdash}is further selected as an actual case study of an urban block and Rhino \& Grasshopper is the platform used to conduct simulation and optimization process with the genetic algorithm. Results showed that in summer, the proposed method can reduce the averaged UTCI from 31.17 to 27.43 {\textdegree}C, a decrease of about 3.74 {\textdegree}C, and reduce mean radiation temperature (MRT) from 43.94 to 41.29 {\textdegree}C, a decrease of about 2.65 {\textdegree}C.

}, keywords = {dry and hot areas; outdoor thermal comfort; urban morphology; urban performance simulation; genetic algorithm-driven}, doi = {10.3390/su11133683}, url = {https://www.mdpi.com/2071-1050/11/13/3683https://www.mdpi.com/2071-1050/11/13/3683/pdf}, author = {Xu, Xiaodong and Yin, Chenhuan and Wang, Wei and Xu, Ning and Hong, Tianzhen and Li, Qi} } @article {31311, title = {Performance-Based Evaluation of Courtyard Design in China{\textquoteright}s Cold-Winter Hot-Summer Climate Regions}, journal = {Sustainability}, volume = {10}, year = {2018}, month = {10/2018}, pages = {3950}, abstract = {

Evaluates the performance of the traditional courtyard design of the Jiangnan Museum, located in Jiangsu Province. In the evaluation, the spatial layout of courtyards is adjusted, the aspect ratio is changed, and an ecological buffer space is created. To model and evaluate the performance of the courtyard design, this study applied the Computational fluid dynamics (CFD) software, Parabolic Hyperbolic Or Elliptic Numerical Integration Code Series (PHOENICS), for wind environment simulation, and the EnergyPlus-based software, DesignBuilder, for energy simulation. Results show that a good combination of courtyard layout and aspect ratio can improve the use of natural ventilation by increasing free cooling during hot summers and reducing cold wind in winters. The results also show that ecological buffer areas of a courtyard can reduce cooling loads in summer by approximately 19.6\% and heating loads in winter by approximately 22.3\%. The study provides insights into the optimal design of a courtyard to maximize its benefit in regulating the microclimate during both winter and summer.

}, keywords = {aspect ratio, courtyard design, ecological buffer area, ecological effect, layout}, doi = {10.3390/su10113950}, url = {http://www.mdpi.com/2071-1050/10/11/3950http://www.mdpi.com/2071-1050/10/11/3950/pdf}, author = {Xiaodong Xu and Fenlan Luo and Wei Wang and Tianzhen Hong and Xiuzhang Fu} } @article {30301, title = {Comparison of typical year and multiyear building simulations using a 55-year actual weather data set from China}, journal = {Applied Energy}, volume = {195}, year = {2017}, month = {06/2017}, pages = {890-904}, abstract = {

Weather has significant impacts on the thermal environment and energy use in buildings. Thus, accurate weather data are crucial for building performance evaluations. Traditionally, typical year data inputs are used to represent long-term weather data. However, there is no guarantee that a single year represents the changing climate well. In this study, the long-term representation of a typical year was assessed by comparing it to a 55-year actual weather data set. To investigate the weather impact on building energy use, 559 simulation runs of a prototype office building were performed for 10 large cities covering all climate zones in China. The analysis results demonstrated that the weather data varied significantly from year to year. Hence, a typical year cannot reflect the variation range of weather fluctuations. Typical year simulations overestimated or underestimated the energy use and peak load in many cases. With the increase in computational power of personal computers, it is feasible and essential to adopt multiyear simulations for full assessments of long-term building performance, as this will improve decision-making by allowing for the full consideration of variations in building energy use.

}, keywords = {Actual weather data, building simulation, energy use, Multiyear simulation, Peak load , Typical year}, doi = {10.1016/j.apenergy.2017.03.113}, author = {Ying Cui and Da Yan and Tianzhen Hong and Chan Xiao and Xuan Luo and Qi Zhang} } @article {30030, title = {A Preliminary Investigation of Water Usage Behavior in Single-Family Homes}, year = {2017}, abstract = {

As regional drought conditions continue deteriorating around the world, residential water use has been brought into the built environment spotlight. Nevertheless, the understanding of water use behavior in residential buildings is still limited. This paper presents data analytics and results from monitoring data of daily water use (DWU) in 50 single-family homes in Texas, USA. The results show the typical frequency distribution curve of the DWU per household and indicate personal income, education level and energy use of appliances all have statistically significant effects on the DWU per capita. Analysis of the water-intensive use demonstrates the residents tend to use more water in post-vacation days. These results help generate awareness of water use behavior in homes. Ultimately, this research could support policy makers to establish a water use baseline and inform water conservation programs.

}, keywords = {daily water use, Data Analytics, occupant behavior, residential water consumption, Water usage behavior}, author = {Peng Xue and Tianzhen Hong and Bing Dong and Cheuk Ming Mak} } @article {59965, title = {Comparison of Building Energy Use Data Between the United States and China}, journal = {Energy and Buildings}, volume = {78}, year = {2014}, month = {08/2014}, pages = {165-175}, abstract = {

Buildings in the United States and China consumed 41\% and 28\% of the total primary energy in 2011, respectively. Good energy data are the cornerstone to understanding building energy performance and supporting research, design, operation, and policy making for low energy buildings. This paper presents initial outcomes from a joint research project under the U.S.{\textendash}China Clean Energy Research Center for Building Energy Efficiency. The goal is to decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current building energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyze good building energy data to provide valuable and actionable information for key stakeholders. This paper first reviews and compares several popular existing building energy monitoring systems in both countries. Next a standard energy data model is presented. A detailed, measured building energy data comparison was conducted for a few office buildings in both countries. Finally issues of data collection, quality, sharing, and analysis methods are discussed. It was found that buildings in both countries performed very differently, had potential for deep energy retrofit, but that different efficiency measures should apply.

}, keywords = {buildings, comparison, data analysis, data model, Energy benchmarking, energy monitoring system, energy use, retrofit}, doi = {10.1016/j.enbuild.2014.04.031}, author = {Jianjun Xia and Tianzhen Hong and Qi Shen and Wei Feng and Le Yang and Piljae Im and Alison Lu and Mahabir Bhandari} } @article {59968, title = {Building Energy Monitoring and Analysis}, year = {2013}, month = {06/2013}, abstract = {

U.S. and China are the world{\textquoteright}s top two economics. Together they consumed one-third of the world{\textquoteright}s primary energy. It is an unprecedented opportunity and challenge for governments, researchers and industries in both countries to join together to address energy issues and global climate change. Such joint collaboration has huge potential in creating new jobs in energy technologies and services.

Buildings in the US and China consumed about 40\% and 25\% of the primary energy in both countries in 2010 respectively. Worldwide, the building sector is the largest contributor to the greenhouse gas emission. Better understanding and improving the energy performance of buildings is a critical step towards sustainable development and mitigation of global climate change.

This project aimed to develop a standard methodology for building energy data definition, collection, presentation, and analysis; apply the developed methods to a standardized energy monitoring platform, including hardware and software, to collect and analyze building energy use data; and compile offline statistical data and online real-time data in both countries for fully understanding the current status of building energy use. This helps decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current building energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyze good building energy data to provide valuable and actionable information for key stakeholders.

Key research findings were summarized as follows:

The research outputs from the project can help better understand energy performance of buildings, improve building operations to reduce energy waste and increase efficiency, identify retrofit opportunities for existing buildings, and provide guideline to improve the design of new buildings. The standardized energy monitoring and analysis platform as well as the collected real building data can also be used for other CERC projects that need building energy measurements, and be further linked to building energy benchmarking and rating/labeling systems.

}, author = {Tianzhen Hong and Wei Feng and Alison Lu and Jianjun Xia and Le Yang and Qi Shen and Piljae Im and Mahabir Bhandari} } @article {421, title = {Technical Assistance to Beichuan Reconstruction: Creating and Designing Low- to Zero-carbon Communities in New Beichuan}, year = {2009}, month = {2009}, institution = {LBNL}, issn = {LBNL-2819E}, url = {http://www.escholarship.org/uc/item/0vv4m1gb}, author = {Tengfang T. Xu and Chuang Wang and Tianzhen Hong and Mark D. Levine} } @proceedings {266, title = {The Building Controls Virtual Test Bed {\textendash} a Simulation Environment for Developing and Testing Control Algorithms, Strategies and Systems}, year = {2007}, address = {Bejing, China}, abstract = {

The paper describes the design of a Building Controls Virtual Test Bed (BCVTB), a simulation environment for the development of control algorithms and strategies for the major energy systems in buildings, HVAC, lighting, active facades and on-site generation. The BCVTB is based on the whole building energy simulation program EnergyPlus and includes both the pure simulation and the hardware-in-the-loop methods of implementing the controls. For convenience and scalability, the design of the hardware-in-the-loop interface for supervisory controls uses BACnet rather than the analog interface used for local loop control. The paper concludes with a case study of the use of a prototype implementation of the BCVTB to precommission the building control system for the naturally-ventilated San Francisco Federal Building. A number of problems were found with the control program, demonstrating the value of the precommissioning and the effectiveness of the technique.

}, keywords = {controls, development system, hardware-in-the-loop, testing}, url = {http://www.ibpsa.org/proceedings/BS2007/p748_final.pdf}, author = {Philip Haves and Peng Xu} } @article {2923, title = {A Semi-automated Commissioning Tool for VAV Air Handling Units: Functional Test Analyzer}, journal = {ASHRAE Transactions}, volume = {113}, number = {Part 1}, year = {2007}, month = {01/2007}, pages = {380-391}, abstract = {

A software tool that automates the analysis of functional tests for air-handling units is described. The tool compares the performance observed during manual tests with the performance predicted by simple models of the components under test that are configured using design information and catalog data. Significant differences between observed and expected performance indicate the presence of faults. Fault diagnosis is performed by analyzing the variation of these differences with operating point using expert rules and fuzzy inferencing.

The tool has a convenient user interface to facilitate manual entry of measurements made during a test. A graphical display compares the measured and expected performance, highlighting significant differences that indicate the presence of faults. The tool is designed to be used by commissioning providers conducting functional tests as part of either new building commissioning or retro-commissioning, as well as by building owners and operators conducting routine tests to check the performance of their HVAC systems. The paper describes the input data requirements of the tool, the software structure, the graphical interface, and summarizes the development and testing process used.

}, url = {http://gaia.lbl.gov/btech/papers/60979.pdf}, author = {Philip Haves and Moosung Kim and Massieh Najafi and Peng Xu} } @article {271, title = {Case Study of Demand Shifting with Thermal Mass in Two Large Commercial Buildings}, journal = {ASHRAE Transactions}, volume = {112}, year = {2006}, chapter = {572}, author = {Peng Xu and Philip Haves} } @proceedings {3394, title = {Evaluation of Demand Shifting Strategies With Thermal Mass in Large Commercial Buildings}, year = {2006}, month = {08/2006}, address = {Cambridge, MA, USA}, author = {Peng Xu} } @proceedings {269, title = {A Library of HVAC Component Models for use in Automated Diagnostics}, year = {2006}, address = {Boston, MA}, abstract = {

The paper describes and documents a library of equipment reference models developed for automated fault detection and diagnosis of secondary HVAC system (air handling units and air distribution systems). The models are used to predict the performance that would be expected in the absence of faults. The paper includes a description of the use of automatic documentation methods in the library.

}, url = {http://www.ibpsa.us/pub/simbuild2006/papers/SB06_034_041.pdf}, author = {Peng Xu and Philip Haves and Dimitri Curtil} } @conference {12052, title = {Measured energy performance of a US-China demonstration energy-efficient commercial building}, booktitle = {2007 ASHRAE Winter Meeting, January 27-31, 2007}, year = {2006}, month = {01/2007}, address = {Dallas, TX}, abstract = {

In July 1998, the U.S. Department of Energy (USDOE) and China{\textquoteright}s Ministry of Science of Technology (MOST) signed a Statement of Work (SOW) to collaborate on the design and construction of an energyefficient demonstration office building and design center to be located in Beijing. The proposed 13,000 m2 (140,000 ft2) nine-story office building would use U.S. energy-efficient materials, space-conditioning systems, controls, and design principles that were judged to be widely replicable throughout China. The SOW stated that China would contribute the land and provide for the costs of the base building, while the U.S. would be responsible for the additional (or marginal) costs associated with the package of energy efficiency andrenewable energy improvements to the building. The project was finished and the building occupied in 2004.

Using DOE-2 to analyze the energy performance of the as-built building, the building obtained 44 out of 69 possible points according to the Leadership in Energy and Environmental Design (LEED) rating, including the full maximum of 10 points in the energy performance section. The building achieved a LEED Gold rating, the first such LEED-rated office building in China, and is 60\% more efficient than ASHRAE 90.1-1999. The utility data from the first year{\textquoteright}s operation match well the analysis results, providing that adjustments are made for unexpected changes in occupancy and operations. Compared with similarly equipped office buildings in Beijing, this demonstration building uses 60\% less energy per floor area. However, compared to conventional office buildings with less equipment and window air-conditioners, the building uses slightly more energy per floor area.

}, author = {Peng Xu and Yu Joe Huang and Ruidong Jin and Guoxiong Yang} } @article {273, title = {Model-Based Automated Functional Testing-Methodology and Application to Air Handling Units}, journal = {ASHRAE Transactions}, volume = {111}, year = {2005}, chapter = {979}, author = {Peng Xu and Philip Haves and Moosung Kim} } @conference {2907, title = {A Semi-Automated Functional Test Data Analysis Tool}, booktitle = {13th National Conference on Building Commissioning}, series = {Proceedings of the 13th National Conference on Building Commissioning}, year = {2005}, address = {New York City, NY}, abstract = {

The growing interest in commissioning is creating a demand that will increasingly be met by mechanical contractors and less experienced commissioning agents. They will need tools to help them perform commissioning effectively and efficiently. The widespread availability of standardized procedures, accessible in the field, will allow commissioning to be specified with greater certainty as to what will be delivered, enhancing the acceptance and credibility of commissioning. In response, a functional test data analysis tool is being developed to analyze the data collected during functional tests for air-handling units.

The functional test data analysis tool is designed to analyze test data, assess performance of the unit under test and identify the likely causes of the failure. The tool has a convenient user interface to facilitate manual entry of measurements made during a test. A graphical display shows the measured performance versus the expected performance, highlighting significant differences that indicate the unit is not able to pass the test. The tool is described as semi-automated because the measured data need to be entered manually, instead of being passed from the building control system automatically. However, the data analysis and visualization are fully automated. The tool is designed to be used by commissioning providers conducting functional tests as part of either new building commissioning or retro-commissioning, as well as building owners and operators interested in conducting routine tests periodically to check the performance of their HVAC systems.

}, author = {Peng Xu and Philip Haves and Moosung Kim} } @conference {1806, title = {A Simulation-Based Testing and Training Environment for Building Controls}, booktitle = {SimBuild 2004, Building Sustainability and Performance Through Simulation}, year = {2005}, month = {08/2004}, address = {Boulder, CO}, abstract = {

A hybrid simulation environment for controls testing and training is described. A real-time simulation of a building and HVAC system is coupled to a real building control system using a hardware interface. A prototype has been constructed and tested in which the dynamic performance of both the HVAC equipment and the building envelope is simulated using SPARK (Simulation Problem Analysis and Research Kernel). A low cost hardware interface between the simulation and the real control system is implemented using plug-in analog-to-digital and digital-to-analog cards in a personal computer. The design and implementation of the hardware interface in SPARK are described. The development of a variant of this environment that uses a derivative of EnergyPlus to test the implementation of a natural ventilation control strategy in real control hardware is also described.

Various applications of the hybrid simulation environment are briefly described, including the development of control algorithms and strategies, control system product testing and the pre-commissioning of building control system installations. The application to the education and training of building operators and HVAC service technicians is discussed in more detail, including the development of a community college curriculum that includes the use of the hybrid simulation environment to teach both control system configuration and HVAC troubleshooting.

}, author = {Peng Xu and Philip Haves and Joseph J Deringer} } @conference {56064, title = {Peak Demand Reduction from Pre-Cooling with Zone Temperature Reset in an Office Building}, booktitle = {2004 ACEEE Summer Study on Energy Efficiency in Buildings}, year = {2004}, month = {08/2004}, address = {Pacific Grove, CA}, abstract = {

The objective of this study was to demonstrate the potential for reducing peak-period electrical demand in moderate-weight commercial buildings by modifying the control of the HVAC system. An 80,000 ft2 office building with a medium-weight building structure and high window-to-wall ratio was used for a case study in which zone temperature set-points were adjusted prior to and during occupancy. HVAC performance data and zone temperatures were recorded using the building control system. Additional operative temperature sensors for selected zones and power meters for the chillers and the AHU fans were installed for the study. An energy performance baseline was constructed from data collected during normal operation. Two strategies for demand shifting using the building thermal mass were then programmed in the control system and implemented progressively over a period of one month. It was found that a simple demand limiting strategy performed well in this building. This strategy involved maintaining zone temperatures at the lower end of the comfort region during the occupied period up until 2 pm. Starting at 2 pm, the zone temperatures were allowed to float to the high end of the comfort region. With this strategy, the chiller power was reduced by 80-100\% (1 - 2.3 W/ft2) during normal peak hours from 2 - 5 pm, without causing any thermal comfort complaints. The effects on the demand from 2 - 5 pm of the inclusion of pre-cooling prior to occupancy are unclear.

}, keywords = {demand shifting (pre-cooling)}, author = {Peng Xu and Philip Haves and Mary Ann Piette and James E. Braun} } @proceedings {282, title = {A simulation-based testing and training environment for building controls}, year = {2004}, address = {Boulder, CO}, abstract = {

A hybrid simulation environment for controls testing and training is described. A real-time simulation of a building and HVAC system is coupled to a real building control system using a hardware interface. A prototype has been constructed and tested in which the dynamic performance of both the HVAC equipment and the building envelope is simulated using SPARK (Simulation Problem Analysis and Research Kernel). A low cost hardware interface between the simulation and the real control system is implemented using plug-in analog-to-digital and digital-to-analog cards in a personal computer. The design and implementation of the hardware interface in SPARK are described. The development of a variant of this environment that uses a derivative of EnergyPlus to test the implementation of a natural ventilation control strategy in real control hardware is also described. Various applications of the hybrid simulation environment are briefly described, including the development of control algorithms and strategies, control system product testing and the pre-commissioning of building control system installations. The application to the education and training of building operators and HVAC service technicians is discussed in more detail, including the development of a community college curriculum that includes the use of the hybrid simulation environment to teach both control system configuration and HVAC troubleshooting.

}, author = {Peng Xu and Philip Haves and Joseph J Deringer} } @article {2908, title = {An automated functional test and fault detection method}, year = {2003}, author = {Peng Xu and Moosung Kim and Philip Haves} } @article {260, title = {Computer Measurement and Automation System for Gas-fired Heating Furnace}, journal = {Journal of Harbin Institute of Technology (Chinese)}, volume = {35}, year = {2003}, pages = {374-378}, author = {Xiufeng Pang and Yongcheng Jiang and Yan-shu Miao and Jun Xiong} } @article {1563, title = {Library of component reference models for fault detection}, year = {2003}, author = {Peng Xu and Philip Haves} } @proceedings {299, title = {Field Testing of Component-Level Model-Based Fault Detection Methods for Mixing Boxes and VAV Fan Systems}, year = {2002}, month = {08/2002}, address = {Asilomar, California, USA}, abstract = {

An automated fault detection and diagnosis tool for HVAC systems is being developed, based on an integrated, lifecycle, approach to commissioning and performance monitoring. The tool uses component-level HVAC equipment models implemented in the SPARK equation-based simulation environment. The models are configured using design information and component manufacturers{\textquoteright} data and then fine-tuned to match the actual performance of the equipment by using data measured during functional tests of the sort using in commissioning. This paper presents the results of field tests of mixing box and VAV fan system models in an experimental facility and a commercial office building. The models were found to be capable of representing the performance of correctly operating mixing box and VAV fan systems and detecting several types of incorrect operation.

}, author = {Peng Xu and Philip Haves} } @conference {2955, title = {Field Testing of Component-Level Model-Based Fault Detection Methods for Mixing Boxes and VAV Fan Systems}, booktitle = {2002 American Council for an Energy-Efficient Economy Summer Study on Energy Efficiency in Buildings}, year = {2002}, month = {05/2002}, address = {Pacific Grove, California}, abstract = {

An automated fault detection and diagnosis tool for HVAC systems is being developed, based on an integrated, life-cycle, approach to commissioning and performance monitoring. The tool uses component-level HVAC equipment models implemented in the SPARK equation-based simulation environment. The models are configured using design information and component manufacturers{\textquoteright} data and then fine-tuned to match the actual performance of the equipment by using data measured during functional tests of the sort using in commissioning. This paper presents the results of field tests of mixing box and VAV fan system models in an experimental facility and a commercial office building. The models were found to be capable of representing the performance of correctly operating mixing box and VAV fan systems and detecting several types of incorrect operation.

}, author = {Peng Xu and Philip Haves} } @proceedings {297, title = {HVAC Component Data Modeling Using Industry Foundation Classes}, year = {2002}, month = {12/2002}, address = {Li{\`e}ge, Belgium}, abstract = {

The Industry Foundation Classes (IFC) object data model of buildings is being developed by the International Alliance for Interoperability (IAI). The aim is to support data sharing and exchange in the building and construction industry across the life-cycle of a building.

This paper describes a number of aspects of a major extension of the HVAC part of the IFC data model. First is the introduction of a more generic approach for handling HVAC components. This includes type information, which corresponds to catalog data, occurrence information, which defines item-specific attributes such as location and connectivity, and performance history information, which documents the actual performance of the component instance over time. Other IFC model enhancements include an extension of the connectivity model used to specify how components forming a system can be traversed and the introduction of time-based data streams.

This paper includes examples of models of particular types of HVAC components, such as boilers and actuators, with all attributes included in the definitions. The paper concludes by describing the on-going process of model testing, implementation and integration into the complete IFC model and how the model can be used by software developers to support interoperability between HVAC-oriented design and analysis tools.

}, author = {Vladimir Bazjanac and James Forester and Philip Haves and Darko Sucic and Peng Xu} }